Container scaling at Solidify

Container scaling and challenges along the way

Containers has exploded in both extent and capacity lately, especially when it comes to cloud services. One big advantage is its architecture and the fact that it now exists standards for how to distribute applications or object on containers. By breaking down applications, you get the possibility to place them on different physical and virtual machines, regardless of whether you’re working in the cloud or not. This in turn leads to more flexibility and workload management. It also helps with container scaling and when using containers in bigger projects.

Another big advantage of containers is that as popularity rises, so has the interest of large organizations. Amazon Web Services (AWS), IBM’s Bluemix and Microsoft’s Azure Container Service are just a few examples. There is no doubt that containers is the real deal.

We’ve seen that containers create ways to manage and distribute an application of different environments without needing to worry about making any changes to the application itself. They also make deployment automation simple, increases capacity and reduces complexity. We’ve previously written about other advantages, Docker and Microsoft’s role, but what does this mean for software developers and how do you take containers to the next level?

Container scaling

There are two main alternatives for you who want to scale up using containers. The first option is to create your own customized system for container management – a system that automatically handles container creation, deployment and anything else you might need. Remember that this type of alternative often costs a lot of time and effort to maintain quality.

The other alternative is to use already existing technologies for handling, scheduling and clustering, that often include basic mechanisms for scaling. This tends to be the better option for container scaling.

In regards to option two there are a lot of different tools such as Docker Swarm, Kubernetes and Mesos. These have different advantages and there are situations where one particular tool might be more fitting than the other. However, there are a handful of general tips to always consider when thinking about container scaling.

  • Make sure to spend time on container based application architecture. Most problems associated with scaling can be traced back tp problematic design rather than technologies.
  • Validate the concept to determine the actual possibilities for scaling up. Use tools for automated testing to simulate workload and big amounts of data.
  • Think about your own system requirements. Just because something works for another organization, doesn’t it mean that it’s right for your applications.
  • Don’t forget security or governance – these also needs to be scaled up.


Even with all the advantages containers bring, there are a few challenges to keep in mind:

  • Some applications simply doesn’t fit for container usage. In case your application is small and simple, introducing containers can cause increased complexity and be a waste of time.
  • Sometimes virtual machines are needed instead of containers. As containers is bound to the underlying operating systems, you cannot run a Linux container on a Windows server, for example.
  • It’s easy to create a mess in the cloud. Since containers are so simple to create, you run the risk of using more resources than you actually need.
  • Weaker isolation can cause security flaws. In case anyone could find a flaw in the operating system, they could also reach the container and vice versa.

There is still a lot to explore in regards to containers. However, the question is probably not whether or not containers will be used anymore, but rather how to best use them for each specific scenario.


Have you managed to scale up using containers, or faced any challenges left out in the list? Let us know in the comments below!

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